Category: Diet

BIA lean body mass evaluation

BIA lean body mass evaluation

Correspondence to Charles F Saladino. Outcomes The primary outcome was the time course of muscle atrophy, evalustion using BIA lean body mass evaluation and two BIA devices. Kass, A. Figure S5. There are many methods that can estimate muscle mass. The technique selection will depend on the clinical context, hardware, and knowledge availability. Contrary to the cells of the BCM, fat cells have hardly any metabolic activity and cannot be detected by phase sensitive measurements because of their minimal membrane potential.

BIA lean body mass evaluation -

BIA, L3-targeted CT, and DEXA could be used for the assessment of nutritional status, the calculation of energy needs, and the tailoring of nutritional support and therapy. Further studies are warranted to validate BIA as an accurate method for fluid balance measurement. By integrating body composition evaluation into the management of different clinical conditions, all of these potential applications would lead to a better recognition of nutritional care by the medical community, the health care facilities, and the health authorities, as well as to an increase in the medico-economic benefits of the nutritional evaluation.

Academic societies encourage systematic screening of undernutrition at hospital admission and during the hospital stay [ 14 ]. The detection of undernutrition is generally based on measurements of weight and height, calculations of BMI, and the percentage of weight loss. Nevertheless, screening of undernutrition is infrequent in hospitalized or nutritionally at-risk ambulatory patients.

Several issues, which could be improved by specific educational programs, explain the lack of implementation of nutritional screening in hospitals table 1. In addition, the accuracy of the clinical screening of undernutrition could be limited at hospital admission.

Indeed, patients with undernutrition may have the same BMI as sex- and age-matched healthy controls but a significantly decreased FFM hidden by an expansion of the FM and the total body water which can be measured by bioelectrical impedance analysis BIA [ 13 ].

This example illustrates that body composition evaluation allows a more accurate identification of FFM loss than body weight loss or BMI decrease. The lack of sensitivity and specificity of weight, BMI, and percentage of weight loss argue for the need for other methods to evaluate the nutritional status.

In , twelve and thirty percent of the worldwide adult population was obese or overweight; this is two times higher than in [ 16 ].

The prevalence of overweight and obesity is also increasing in hospitalized patients. The BMI increase masks undernutrition and FFM loss at hospital admission. Sarcopenic obesity is characterized by increased FM and reduced FFM with a normal or high body weight. The emergence of the concept of sarcopenic obesity will increase the number of situations associated with a lack of sensitivity of the calculations of BMI and body weight change for the early detection of FFM loss.

This supports a larger use of body composition evaluation for the assessment and follow-up of nutritional status in clinical practice fig. Body composition evaluation is a valuable technique to assess nutritional status.

Firstly, it gives an evaluation of nutritional status through the assessment of FFM. Secondly, by measuring FFM and phase angle with BIA, it allows evaluation of the disease prognosis and outcome.

Body composition evaluation allows measurement of the major body compartments: FFM including bone mineral tissue , FM, and total body water. Table 2 shows indicative values of the body composition of a healthy subject weighing 70 kg. In several clinical situations, i. At hospital admission, body composition evaluation could be used for the detection of FFM loss and undernutrition.

Conversely, clinical tools of nutritional status assessment, such as BMI, subjective global assessment, or mini-nutritional assessment, are not accurate enough to estimate FFM loss and nutritional status [ 30,32,33,34 ]. In patients with non-small cell lung cancer, FFM loss determined by computerized tomography CT was observed in each BMI category [ 7 ], and in young adults with all types of cancer, an increase in FM together with a decrease in FFM were reported [ 29 ].

These findings reveal the lack of sensitivity of BMI to detect FFM loss. In COPD, the assessment of FFM by BIA is a more sensitive method to detect undernutrition than anthropometry [ 33,35 ]. BIA is also more accurate at assessing nutritional status in children with severe neurologic impairment than the measurement of skinfold thickness [ 36 ].

Mean values of body composition compartments adapted from Pichard and Kyle [ 19 and Wang et al. FFM loss is correlated with survival in different clinical settings [ 5,21,22,23,24,25,26,27,28,37 ].

In patients with amyotrophic lateral sclerosis, an FM increase, but not an FFM increase, measured by BIA, was correlated with survival during the course of the disease [ 28 ]. The relation between body composition and mortality has not yet been demonstrated in the intensive care unit.

The relation between body composition and mortality has been demonstrated with anthropometric methods, BIA, and CT.

Measurement of the mid-arm muscle circumference is an easy tool to diagnose sarcopenia [ 38 ]. The mid-arm muscle circumference has been shown to be correlated with survival in patients with cirrhosis [ 39,40 ], HIV infection [ 41 ], and COPD in a stronger way than BMI [ 42 ].

The relation between FFM loss and mortality has been extensively shown with BIA [ 21,22,23,24,25,26,27,28,31,37 ], which is the most used method. Recently, very interesting data suggest that CT could evaluate the disease prognosis in relation to muscle wasting. In obese cancer patients, sarcopenia as assessed by CT measurement of the total skeletal muscle cross-sectional area is an independent predictor of the survival of patients with bronchopulmonary [ 5,7 ], gastrointestinal [ 5 ], and pancreatic cancers [ 6 ].

FFM assessed by measurement of the mid-thigh muscle cross-sectional area by CT is also predictive of mortality in COPD patients with severe chronic respiratory insufficiency [ 43 ]. In addition to mortality, a low FFMI at hospital admission is significantly associated with an increased LOS [ 3,44 ].

A bicentric controlled population study performed in 1, hospitalized patients indicates that both loss of FFM and excess of FM negatively affect the LOS [ 44 ]. Patients with sarcopenic obesity are most at risk of increased LOS.

This study also found that excess FM reduces the sensitivity of BMI to detect nutritional depletion [ 44 ]. Together with the observation that the BMI of hospitalized patients has increased during the last decade [ 17 ], these findings suggest that FFM and FFMI measurement should be used to evaluate nutritional status in hospitalized patients.

BIA measures the phase angle [ 45 ]. The phase angle threshold associated with reduced survival is variable: less than 2. The phase angle is also associated with the severity of lymphopenia in AIDS [ 56 ], and with the risk of postoperative complications among gastrointestinal surgical patients [ 57 ].

The relation of phase angle with prognosis and disease severity reinforces the interest in using BIA for the clinical management of patients with chronic diseases at high risk of undernutrition and FFM loss. In summary, FFM loss or a low phase angle is related to mortality in patients with chronic diseases, cancer including obesity cancer patients , and elderly patients in long-stay facilities.

A low FFM and an increased FM are associated with an increased LOS in adult hospitalized patients. The relation between FFM loss and clinical outcome is clearly shown in patients with sarcopenic obesity.

In these patients, as the sensitivity of BMI for detecting FFM loss is strongly reduced, body composition evaluation appears to be the method of choice to detect undernutrition in routine practice.

Overall, the association between body composition, phase angle, and clinical outcome reinforces the pertinence of using a body composition evaluation in clinical practice. Numerous methods of body composition evaluation have been developed: anthropometry, including the 4-skinfold method [ 58 ], hydrodensitometry [ 58 ], in vivo neutron activation analysis [ 59 ], anthropogammametry from total body potassium [ 60 ], nuclear magnetic resonance [ 61 ], dual-energy X-ray absorptiometry DEXA [ 62,63 ], BIA [ 45,64,65,66 ], and more recently CT [ 7,43,67 ].

DEXA, BIA, and CT appear to be the most convenient methods for clinical practice fig. Compared with other techniques of body composition evaluation, the lack of reproducibility and sensitivity of the 4-skinfold method limits its use for the accurate measurement of body composition in clinical practice [ 33,34 ].

However, in patients with cirrhosis [ 39,40 ], COPD [ 34 ], and HIV infection [ 41 ], measurement of the mid-arm muscle circumference could be used to assess sarcopenia and disease-related prognosis. DEXA allows noninvasive direct measurement of the three major components of body composition.

The measurement of bone mineral tissue by DEXA is used in clinical practice for the diagnosis and follow-up of osteoporosis. As the clinical conditions complicated by osteoporosis are often associated with undernutrition, i.

elderly women, patients with organ insufficiencies, COPD [ 68 ], inflammatory bowel diseases, and celiac disease, DEXA could be of the utmost interest for the follow-up of both osteoporosis and nutritional status. However, the combined evaluation of bone mineral density and nutritional status is difficult to implement in clinical practice because the reduced accessibility of DEXA makes it impossible to be performed in all nutritionally at-risk or malnourished patients.

The principles and clinical utilization of BIA have been largely described in two ESPEN position papers [ 45,66 ]. BIA is based on the capacity of hydrated tissues to conduct electrical energy.

The measurement of total body impedance allows estimation of total body water by assuming that total body water is constant. From total body water, validated equations allow the calculation of FFM and FM [ 69 ], which are interpreted according to reference values [ 70 ].

BIA is the only technique which allows calculation of the phase angle, which is correlated with the prognosis of various diseases. BIA equations are valid for: COPD [ 65 ]; AIDS wasting [ 71 ]; heart, lung, and liver transplantation [ 72 ]; anorexia nervosa [ 73 ] patients, and elderly subjects [ 74 ].

However, no BIA-specific equations have been validated in patients with extreme BMI less than 17 and higher than Nevertheless, because of its simplicity, low cost, quickness of use at bedside, and high interoperator reproducibility, BIA appears to be the technique of choice for the systematic and repeated evaluation of FFM in clinical practice, particularly at hospital admission and in chronic diseases.

Finally, through written and objective reports, the wider use of BIA should allow improvement of the traceability of nutritional evaluation and an increase in the recognition of nutritional care by the health authorities.

Recently, several data have suggested that CT images targeted on the 3rd lumbar vertebra L3 could strongly predict whole-body fat and FFM in cancer patients, as compared with DEXA [ 7,67 ].

Interestingly, the evaluation of body composition by CT presents great practical significance due to its routine use in patient diagnosis, staging, and follow-up.

The muscles included in the calculation of the muscle cross-sectional area are psoas, paraspinal muscles erector spinae, quadratus lumborum , and abdominal wall muscles transversus abdominis, external and internal obliques, rectus abdominis [ 6 ].

CT also provided detail on specific muscles, adipose tissues, and organs not provided by DEXA or BIA. L3-targeted CT images could be theoretically performed solely, since they result in X-ray exposition similar to that of a chest radiography. In summary, DEXA, BIA, and L3-targeted CT images could all measure body composition accurately.

The technique selection will depend on the clinical context, hardware, and knowledge availability. Body composition evaluation by DEXA should be performed in patients having a routine assessment of bone mineral density. Also, analysis of L3-targeted CT is the method of choice for body composition evaluation in cancer patients.

Body composition evaluation should also be done for every abdominal CT performed in patients who are nutritionally at risk or undernourished. Because of its simplicity of use, BIA could be widely implemented as a method of body composition evaluation and follow-up in a great number of hospitalized and ambulatory patients.

Future research will aim to determine whether a routine evaluation of body composition would allow early detection of the increased FFM catabolism related to critical illness [ 75 ].

The evaluation of FFM could be used for the calculation of energy needs, thus allowing the optimization of nutritional intakes according to nutritional needs. This could be of great interest in specific situations, such as severe neurologic disability, overweight, and obesity.

In 61 children with severe neurologic impairment and intellectual disability, an equation integrating body composition had good agreement with the doubly labeled water method.

It gave a better estimation of energy expenditure than did the Schofield predictive equation [ 36 ]. However, in 9 anorexia nervosa patients with a mean BMI of In overweight or obese patients, the muscle catabolism in response to inflammation was the same as that observed in patients with normal BMI.

Indeed, despite a higher BMI, the FFM of overweight or obese individuals is similar or slightly increased to that of patients with normal BMI. Thus, the use of actual weight for the assessment of the energy needs of obese patients would result in overfeeding and its related complications. Thus, follow-up of FFM by BIA could help optimize nutritional intakes when indirect calorimetry cannot be performed.

Body composition evaluation allows a qualitative assessment of body weight variations. Body composition evaluation could be used for the follow-up of healthy elderly subjects [ 90 ]. Body composition evaluation allows characterization of the increase in body mass in terms of FFM and FM [ 81,91 ].

After hematopoietic stem cell transplantation, the increase in BMI is the result of the increase in FM, but not of the increase in FFM [ 81 ].

By identifying the patients gaining weight but reporting no or insufficient FFM, body composition evaluation could contribute to influencing the medical decision of continuing nutritional support that would have been stopped in the absence of body composition evaluation.

In summary, body composition evaluation is of the utmost interest for the follow-up of nutritional support and its impact on body compartments.

This point has been recently illustrated in oncology patients with sarcopenic obesity. FFM loss was determined by CT as described above. In cancer patients, some therapies could affect body composition by inducing muscle wasting [ 92 ].

In turn, muscle wasting in patients with BMI less than 25 was significantly associated with sorafenib toxicity in patients with metastatic renal cancer [ 8 ]. In metastatic breast cancer patients receiving capecitabine treatment, and in patients with colorectal cancer receiving 5-fluoro-uracile, using the convention of dosing per unit of body surface area, FFM loss was the determinant of chemotherapy toxicity [ 9,10 ] and time to tumor progression [ 10 ].

In colorectal cancer patients administered 5-fluoro-uracil, low FFM is a significant predictor of toxicity only in female patients [ 9 ]. The variation in toxicity between women and men may be partially explained by the fact that FFM was lower in females. Indeed, FFM represents the distribution volume of most cytotoxic chemotherapy drugs.

In 2, cancer patients, the individual variations in FFM could change by up to three times the distribution volume of the chemotherapy drug per body area unit [ 5 ]. Thus, administering the same doses of chemotherapy drugs to a patient with a low FFM compared to a patient with a normal FFM would increase the risk of chemotherapy toxicity [ 5 ].

These data suggest that FFM loss could have a direct impact on the clinical outcome of cancer patients. These findings justify the systematic evaluation of body composition in all cancer patients in order to detect FFM loss, tailor chemotherapy doses according to FFM values, and then improve the efficacy-tolerance and cost-efficiency ratios of the therapeutic strategies [ 93 ].

corticosteroids, immunosuppressors infliximab, azathioprine or methotrexate , or sedatives propofol. In summary, measurement of FFM should be implemented in cancer patients treated with chemotherapy.

Clinical studies are needed to demonstrate the importance of measuring body composition in patients treated with other medical treatments. The implementation of body composition evaluation in routine care presents a challenge for the next decades.

Indeed the concomitant increases in elderly subjects and patients with chronic diseases and cancer, and in the prevalence of overweight and obesity in the population, will increase the number of patients nutritionally at risk or undernourished, particularly those with sarcopenic obesity.

Body composition evaluation should be used to improve the screening of undernutrition in hospitalized patients. The results could be expressed according to previously described percentiles of healthy subjects [ 95,96 ]. Body composition evaluation should be performed at the different stages of the disease, during the course of treatments and the rehabilitation phase.

BIA, L3-targeted CT, and DEXA represent the techniques of choice to evaluate body composition in clinical practice fig. In the setting of cost-effective and pragmatic use, these three techniques should be alternatively chosen.

In cancer, undernourished, and nutritionally at-risk patients, an abdominal CT should be completed by the analysis of L3-targeted images for the evaluation of body composition.

In other situations, BIA appears to be the simplest most reproducible and less expensive method, while DEXA, if feasible, remains the reference method for clinical practice. By allowing earlier management of undernutrition, body composition evaluation can contribute to reducing malnutrition-induced morbidity and mortality, improving the quality of life and, as a consequence, increasing the medico-economic benefits fig.

The latter needs to be demonstrated. Moreover, based on a more scientific approach, i. The OLP regression analysis revealed a fixed bias in all cases except for percentage of body fat and lean body mass of boys.

Proportional bias was also detected in all cases except for percentage of body fat and lean body mass of boys. Difference plots across the variables from the TOST are reported in Fig. In both boys and girls, the values of fat mass, fat-free mass, percentage of body fat, and lean body mass were between lower and upper bounds.

Two one-sided test of fat mass, fat-free mass, percentage of body fat, lean body mass, bone mineral contents, and body mass in boys.

A summary of the statistical analysis is presented in Table 5. BIA overestimated bone mineral contents boys, For fat mass and fat-free mass, the overestimate or underestimate varied depending on the sex and statistical analysis method. Fat mass, fat-free mass, percentage of body fat, lean body mass, bone mineral contents, and body mass are shown according to BMI category for boys in Table S2 and for girls in Table S3.

The ICCs were excellent or good for fat-free mass, lean body mass, and body mass in all quartiles in both boys and girls. The ICCs for bone mineral content were poor in all quartiles in both boys and girls.

Bland—Altman plots of each BMI category are shown in Figs. S1—S4 for both sexes. Fat mass, fat-free mass, percentage of body fat, lean body mass, bone mineral contents, and body mass are shown according to grade for boys in Table S4 and for girls in Table S5. The ICCs were excellent or good for fat mass, fat-free mass, percentage of body fat, lean body mass, and body mass in both boys and girls, except for percentage of body fat in 8th grade boys.

The ICCs for bone mineral content were poor in all grades in both boys and girls. Bland—Altman plots of each grade are shown in Figs.

S5—S8 for both sexes. Our results showed significant differences in the values of all parameters between BIA and DXA, with this being the case for boys, girls, and all participants.

In addition, BIA overestimated bone mineral contents for boys, girls, and all participants, and underestimated lean body mass, body mass, and percentage of body fat. However, the differences in fat mass, fat-free mass, lean body mass, bone mineral contents, and body mass were within 1 kg for boys, girls, and all participants, with the exception of lean body mass for girls, which showed a small difference of 1.

Lee et al. performed DXA and single-frequency and multi-frequency BIA measurements on children aged 7—12 years and reported significant differences in lean body mass, fat mass, and percentage of body fat between single frequency BIA, multi-frequency BIA, and DXA BIA overestimated lean body mass, and underestimated fat mass and percentage of body fat Larsen et al.

measured fat mass and lean body mass with multi-frequency BIA and DXA in children aged 10—12 years and reported that the measurements were significantly different between BIA and DXA, and that BIA underestimated both fat mass and lean body mass The results of the present study also revealed significant differences between DXA and BIA, consistent with previous results.

Regarding the magnitude of the differences in measurements between DXA and single-frequency BIA, Lee et al. reported differences of lean body mass, fat mass, and percentage of body fat of 2.

Compared with these results, the differences between DXA and BIA measurements found in our study are small. reported differences between DXA and multi-frequency BIA measurements of 2.

reported differences in the mean lean body mass, fat mass, and percentage of body fat between DXA and BIA measurements of 0. The differences between multi-frequency BIA and DXA found in our study are comparable to these previous results. When we checked the concordance of the ICCs and CCCs, we found that the values for fat mass, fat-free mass, lean body mass, and body mass were all more than 0.

reported that for boys and girls, the ICCs between single or multi-frequency BIA and DXA for lean body mass, fat mass, and percentage of body fat were all above 0. In addition, all CCCs were above 0. In previous studies, CCCs for fat mass and fat-free mass in children were above 0.

For percentage of body fat, the CCCs ranged from 0. A study by Seo et al. with Korean boys and girls 6—17 years showed similar results Compared with the results of these previous studies, the BIA measurements obtained in this study showed a strong linear relationship with DXA and a high degree of agreement for fat mass, fat-free mass, and lean body mass.

In this study, we also used the equivalence testing method 36 , 53 to assess measurement agreement. Previously, only Larsen et al. performed TOSTs to evaluate the agreement of fat mass between DXA and multi-frequency BIA in children In their study, they used the same equivalence interval as we did 19 , 38 , but while we found that the values of fat mass, fat-free mass, and body mass in both sexes, lean body mass in boys and percentage of body fat in girls, were between lower and upper bounds, the multi-frequency BIA used in the previous study found no agreement These results indicate that the agreement between DXA and the single-frequency BIA used in the present study was not inferior to that between DXA and multi-frequency BIA.

Furthermore, in the Bland—Altman analysis, the limits of agreement were similar or smaller than in previous studies 19 , 20 , In contrast, most of the indicators showed fixed and proportional bias, and many indices show fixed biases and proportional biases in the results of the OLP regression analysis.

The fact that both biases were observed in Bland—Altman analysis and OLP regression analysis indicates that absolute agreement was not always obtained, and that the values measured by BIA are not exact substitutes for DXA values. However, the small limits of agreement in the Bland—Altman analysis suggest that BIA can be used for health management purposes in daily life if the characteristics observed in this study are taken into account.

In contrast to the parameters mentioned above, bone mineral contents showed low ICCs, CCCs, and absolute agreements. For percentage of body fat, the ICCs or CCCs were below 0.

However, the absolute agreements for fat mass, fat-free mass, lean body mass, and body mass were good, indicating that these BIA indices are reliable enough for daily use.

In addition, BIA overestimated bone mineral content and underestimated percentage of body fat, lean body mass, and body mass. Chiplonkar et al. reported that BIA overestimated fat mass, fat-free mass, and lean mass compared with DXA whereas underestimated percentage body fat Lopez-Gonzalez et al.

reported that BIA overestimated fat-free mass, but underestimated fat mass and percentage of body fat relative to DXA Seo et al.

reported that BIA overestimated fat-free mass and underestimated percentage of body fat and fat mass compared with DXA From these studies, overestimation or underestimation may depends on the particular BIA device used to make the measurements.

In BIA, fat-free mass is estimated from electrical resistance values, from which fat mass, percentage of body fat, bone mineral contents, and lean body mass are calculated Therefore, while accurate fat-free mass values are obtained directly, the other values are estimated from these fat-free mass values.

The BIA device utilized in this study used a single-frequency of 50 kHz, which may result in inaccurate estimates of other indices compared with fat-free mass, because the evaluation of extracellular fluid and intracellular fluid is inferior compared with multi-frequency BIA However, we also showed that our measurement results were not inferior to those of other studies using multi-frequency BIA.

This may be because the BIA device that we used utilizes an eight-pole electrode, and although it is a single frequency device, it uses reactance technology that allows impedance to be broken down into resistance and reactance, making it more accurate than conventional four-pole electrode BIA.

The DXA method uses the rate of attenuation of radiation irradiated to a living body to quantify bone mineral content 56 , whereas BIA measures electrical resistance that does not directly quantify bone mineral content In addition, recent BIA measurement methods are based on a multi-compartment model that calculates extracellular fixations, excluding body fat, body cell mass, and extracellular fluid 14 , In BIA, extracellular fixations are indicated as bone mineral content, which is the reason why BIA overestimates bone mineral contents in comparison with DXA.

Therefore, compared with other indices, the bone mineral contents showed a greater discrepancy between BIA and DXA measurements, and also showed lower absolute concordance values such as ICC and CCC. However, relative concordance was found, and a considerable degree of relative concordance was obtained in sub group analyses by sex and BMI, and because BIA overestimated values, it would be possible not to provide clinical information but to observe bone mineral contents to a certain extent using the same BIA instrument for the purpose of daily health management.

The participants in this study had a wide range of BMI, and we therefore divided them into four categories according to sex and BMI and performed separate analyses in each category.

The results showed a high relative agreement for all indicators in the top three BMI categories of both sexes. However, the relative agreement for percentage of body fat was low in the lowest BMI category for both boys and girls.

In terms of absolute concordance, both ICCs and CCCs showed high concordance for body mass, fat-free mass, and lean body mass in most categories, although absolute agreement was low for bone mineral contents, in contrast to the relatively good relative agreement observed.

Bland—Altman analysis of each index according to sex and BMI showed fixed and proportional bias for many indices, indicating that while the impedance method generally provides relative agreement, absolute agreement is limited to body mass and fat-free mass.

The results for fat mass and percentage of body fat showed particularly poor agreement in the low BMI category. Because body mass measures total mass regardless of body composition, it is easy to make accurate measurements with commercially available scales, which explains the high concordance in body mass shown in this study.

We also performed separate analyses in each grade. The results showed the high relative agreement for all indicators in all grades of both sexes.

In terms of absolute concordance, both ICCs and CCCs showed high concordance for fat mass, fat-free mass, lean body mass, and body mass in most grades, although absolute agreement was low for bone mineral contents.

Bland—Altman analysis of each index according to sex and grade showed fixed and proportional bias for many indices. These results are similar to those obtained in the analysis by BMI category.

However, there were no distinct differences in results between grades whereas there were differences in results between BMI categories. Total body water TBW is one of most important factors for BIA analysis. TBW changes according to the height, body mass, body surface area, and age.

However, the association of TBW with height, body mass, and body surface are strong compared to that with age 58 , which may explain the present results. In the present study, as in many other studies, DXA was used as the reference with which the BIA method was compared.

However, the algorithm used in DXA is based on adult proportions and may not be accurate in children This is because the water content and body density of the fat-free mass of children is different to that of adults and changes throughout growth Therefore, to use DXA as a reference value for measurements in children, the DXA algorithm should be based on the proportions of the child, and it is also better if it is based on each growth stage of the child.

This study had several limitations and strengths. The first limitation was that the participants of the present study were children of a limited age range living in a limited region of Japan; thus, it is necessary to investigate children in other regions and of other ages in order to generalize the present results.

Second, this study does not take into account the effects of physiological diurnal variation; that is, not all participants in this study were measured at the same time of day, and therefore diurnal variations may be reflected in the results.

Although diurnal variation has not been studied with the same BIA device as that used in the present study, Andersen et al. In addition, the impedance method was measured only once in the present study, although the BIA device itself has been reported as being reliable in respect to measurement error Third, the hydration status of the participants, room temperature and humidity, presence or absence of menarche, and the period of the menstrual cycle, were not measured.

The BIA method is considered to be influenced by these factors, which may have had some influences on the present results. Therefore, the heights in the present study may have been affected by diurnal variation.

In contrast, the strengths of this study are that it is a population-based study, that we adopted various statistical analysis methods for comparisons between BIA and DXA, and provide precise results of these comparison.

In this study, we examined the usefulness of a commercially available bioelectrical impedance device by comparing its results with those obtained using a DXA method. Our results revealed strong linear correlations between BIA and DXA, which confirmed the validity of the BIA-derived parameters calculated in this study.

However, we also showed that measurement bias exists in all indices and that it varies with sex and degree of BMI. These findings suggest that the BIA device cannot provide the exact same body composition values as DXA, but that it has sufficient measurement performance to be used longitudinally by individuals for daily health management.

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Body water and lean body mass appear too large, and calculations of the body fat will appear as too low in the results.

It is important to remember that the human body is never static, but functions with the help of a dynamic system, and that changes of the body water occur hourly and change on a daily basis.

A current B. can therefore only be a snapshot of a dynamic system and of the condition at that point in time. That's why several repeat and response measurements of the individual will provide a more accurate picture and improve the assessment of body composition.

Reactance The resistance that a condenser exerts to an alternating current is called Reactance Xc. Due to their protein-lipid layers, all cell membranes of the body act like mini-condensers and reactance therefore is an assessment of the body cell mass.

General Principles Bioelectric impedance measurements BIM is the term representative for a variety of traditional and new noninvasive procedures and technologies that use electric current. With the help of one or more surface electrodes, a tiny amount of electrical current is activated and is detected at surface electrodes placed elsewhere on the body, once the resultant electricity pulse has passed through.

As it quickly proceeds through the various physiological sections of the body, and passes through, a drop in voltage occurs. The current encounters impedance or resistance inherent in the fluids and tissues it passes through the various areas, among them the intracellular space, the lymphatic system, the bloodstream and others.

The drop in voltage delivers indirect information about the physical properties of the sections, where current has passed through. Alternating Current Bioelectric Impedance Analysis BIA : Among the various number of A.

BIA models that are presently on the market, most are used for the obliquely measurement of total body water and to estimate the fat content of the body. BIA, which uses alternating current A.

as the most common form of testing, employs A. Various systems, varying broadly in complexity and design, operate with a wide range of intensities, frequencies and currents. For the patient, the amount of electricity delivered to the body is generally hard to even detect and far below any level that would result in cellular or tissue damage.

Once electric currents at or above 50 KHz are used, they flow non-selectively through extra cellular spaces as well as intracellular ones, as has been confirmed by various A. BIA studies. Once current has been sent to active tactile electrodes at a frequency at 50 KHz, its intensity enables the system to measure the reactance and resistance between 2 other passive tactile electrodes tetra-polar mode.

BIA and Its Calculated Parameters Total Body Water TBW Impedance measurements provide a quite accurate picture of electrolyte water contained in tissue.

Orally ingested water, which has not yet been absorbed by the body, is not measured; the same goes for ascites, because it is not part of the lean body mass.

Administered solutions, however, are detected immediately. Lean Body Mass LBM The lean body mass is for the most part made up of inner organs, muscles, the skeletal system and the central nervous system, and refers to the tissue mass of the body that contains no fat.

These organ systems, although morphologically very different, contain matching functional structures. All of them contain matrix substance and extra-cellular fluids that support the metabolic exchange and assist in substrate transport and are made of cells that execute the synthesis and metabolism processes in the body.

In cases of for example edema or intensive car patients, where the quantity of lean body mass hydration is pathological, irregular calculations may be gathered for body cell mass, lean body mass, and extra-cellular mass - the secondary parameters - and will make the assessment of BIA measurements more difficult.

It helps in these cases, to look at the initial assessment and values for resistance, phase angle and reactance. The lean body mass contains of two subdivisions.

One is the body cell mass BCM, also referred to as the motor of the organism, and the other one is the connective tissues and transport medium, the extra-cellular mass ECM.

Body Cell Mass BCM All tissue of the human organism entails to a certain degree Body cell mass, and the sum of all cells that are actively involved in the metabolic processes is called BCM. While it is rather a functionally defined section and not so much an anatomically one above all, it consists all of the cells of the inner organs and muscles, with the muscles and the highest percentage to constitute the largest part of the BCM.

Connective tissue with low fibrocyte content however only makes up a small percentage of the entire BCM, and adipocytes, due to their low energy metabolism are not at all considered being part of the BCM.

Consequently, the sum of adipocyte cells therefore forms its own compartment in the body. Included in the BCM are the following tissue forms: the smooth muscles, the cells of the skeletal muscle system, the inner organs, the cardiac muscles, the blood, the gastrointestinal tract, the nervous systems and the glands.

As all of the body's metabolic function is performed within the cells of the BCM, the BCM is the main specification for the analysis of a patient's nutritional state.

It is also used as the standard specification for establishing the calorific requirement of the body and for the assessment of energy consumption.

In addition to the catabolism, the BCM also performs work on the anabolism including the keeping up of synthesis and cell structures for the ECM: For example the transportation proteins and enzymes, and the formation of connective tissue fibres, cartilage tissues and bones.

A person's body cell mass is a fractional constituent of the lean body mass, and a number of factors, such as age and physical condition or genetics constitution type play a role in the BCM that is available in an individual. A higher percentage of body cell mass present in lean body mass is for example found in young people with high physical activity, such as competitive athletes.

Their muscles are trained in the maturation phase of the body, and as a result, this higher proportion tends to be found in these individuals throughout their lives persistent hypertrophy of the muscle cells.

Age is also a factor in BCM. Older persons that are active, however, can retain their BCM to a large degree. These are optimal figures for BCM in the lean body mass. In view of the easy measuring methods for the assessment of the body composition, only phase sensitive BIA can be regarded to determine the BCM, and the maintenance of the BCM should be the main goal in any form of nutritional therapy.

A reduction of the body cell mass in BIA happens because of a genuine substantial loss of body cell mass, that can however also be accompanied by a temporary intracellular water loss.

Extra-Cellular Mass ECM The extra-cellular mass ECM is the term for the lean body mass that exists outside the cells of the BCM. Skin, elastin, collagen, tendons, bone and fasciae are the established connective tissue structures of the ECM, with the fluid parts consisting of plasma, interstitial and trans-cellular water.

Trans-cellular water is the description of fluids that are present in the body cavities, for example the contents of the gastro-intestinal lumen and the spinal fluid, while non-physiological trans-cellular fluids appear as ascites, or as pericardial or pleural effusions.

As approx. For example in an ascites of 5 litres, the trunk's resistance would only change by a few ohms, leaving the total resistance practically uninfluenced.

Differences in fat mass that were brought about by weight changes generally appear without a change of resistance, hence the reason why BIA measurements are calculated as changes in fat mass, when it pertains to weight increases caused by ascites or pregnancy.

The assessment of body composition has important applications in Increase mental and physical energy BIA lean body mass evaluation of nutritional status and estimating potential health risks. Bioelectrical impedance analysis Lena is a masx method for the assessment of body masd. BIA is an alternative BIAA more invasive and expensive methods like BIA lean body mass evaluation X-ray absorptiometry, computerized tomography, and magnetic resonance imaging. Bioelectrical impedance analysis is an easy-to-use and low-cost method for the estimation of fat-free mass FFM in physiological and pathological conditions. The reliability of BIA measurements is influenced by various factors related to the instrument itself, including electrodes, operator, subject, and environment. BIA assumptions beyond its use for body composition are the human body is empirically composed of cylinders, FFM contains virtually all the water and conducting electrolytes in the body, and its hydration is constant. FFM can be predicted by BIA through equations developed using reference methods. BIA lean body mass evaluation


What do BIA scales tell you about muscle and body fat?

Author: Fenriran

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